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Remote Machine Vision Engineer Jobs in Wisconsin

Serve Robotics

$225K - $260K/yr

Our personable sidewalk robot is our vision for the future. It's designed to take deliveries away ... Master's or PhD in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a ...

CSAA

Job Title Software Engineer III - AI/ML Platform Operations - Remote Requisition Number R7739 ... Serve as a senior escalation point for complex production issues involving AI platforms, machine ...

CSAA

Job Title Software Engineer III - AI/ML Platform Operations - Remote Requisition Number R7739 ... Serve as a senior escalation point for complex production issues involving AI platforms, machine ...

CSAA

Job Title Software Engineer III - AI/ML Platform Operations - Remote Requisition Number R7739 ... Serve as a senior escalation point for complex production issues involving AI platforms, machine ...

CSAA

Job Title Software Engineer III - AI/ML Platform Operations - Remote Requisition Number R7739 ... Serve as a senior escalation point for complex production issues involving AI platforms, machine ...

Pro Mach, Inc.

Field Service Engineer

Middleton, WI · On-site +1

Train customers' operators and technicians on machine setup, operation, change-over, and ... Provide technical support and assistance to customers via phone, remote connection, or on-site for ...

Qualysoft

... to-End Machine-Learning-Workflows von der Entwicklung bis zum produktiven Einsatz ... Remote bevorzugt, gelegentliche Vor-Ort-Termine nach Absprache 400 - 450 a day Aufgaben Aufbau und ...

Qualysoft

Hybrid - ca. 50 % vor Ort in Wien, ca. 50 % remote Projektsprache: Deutsch und Englisch Aufgaben: ... Machine-Learning-Frameworks wie TensorFlow, PyTorch und scikit-learn Praktische Erfahrung im Big ...

Sterling Engineering Inc.

Project Engineer

Madison, WI · On-site +1

$115K/yr

Medical, Dental, Vision Pay: Up to $115K (Depending on Experience) Job Summary: Sterling is seeking ... Primarily remote with occasional travel to client meetings. Qualified applicants will receive ...

EnsoData

Backend Software Engineer

Madison, WI · On-site +1

Using AI and machine learning, our software analyzes billions of data points collected from sensors ... Remote and flexible schedule - we are a remote company with hybrid options and support for flexible ...

New

Tartan Solutions

$52 - $71.25/hr

Deploy new machines as required to meet demand. Automate where possible. * Manage SSL certificates ... Strong familiarity with DevOps processes and approaches, especially with GitOps Kubernetes ...

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Remote Machine Vision Engineer information

How do Remote Machine Vision Engineers typically collaborate with cross-functional teams given the remote nature of the role?

Remote Machine Vision Engineers often work closely with software developers, hardware engineers, and project managers through virtual meetings, collaborative platforms, and shared code repositories. Effective communication is essential to ensure alignment on project goals, technical specifications, and integration challenges. Regular video conferences, clear documentation, and agile project management tools help maintain productivity and foster team cohesion, despite being geographically dispersed.

What does a Remote Machine Vision Engineer do?

A Remote Machine Vision Engineer designs, develops, and implements computer vision systems that enable machines to interpret visual information, often working from a remote location. Their tasks include creating algorithms for image processing, integrating hardware like cameras, and collaborating with teams to solve automation or inspection challenges. They may work in industries such as manufacturing, robotics, or healthcare, using technologies like deep learning and neural networks. Remote Machine Vision Engineers typically use tools such as Python, OpenCV, and TensorFlow, and communicate with their teams via digital platforms. This role requires both strong programming skills and a deep understanding of image analysis techniques.

What are the key skills and qualifications needed to thrive as a Remote Machine Vision Engineer, and why are they important?

To thrive as a Remote Machine Vision Engineer, you need expertise in computer vision, image processing, programming (such as Python or C++), and a relevant engineering or computer science degree. Familiarity with frameworks like OpenCV, deep learning libraries (TensorFlow or PyTorch), and experience with cloud-based collaboration tools are typically required. Strong problem-solving abilities, self-motivation, and effective remote communication skills help you excel in this role. These skills ensure the accurate design and deployment of vision solutions while maintaining productivity and collaboration in a remote work environment.
What are the most commonly searched types of Machine Vision Engineer jobs in Wisconsin? The most popular types of Machine Vision Engineer jobs in Wisconsin are:
What are popular job titles related to Remote Machine Vision Engineer jobs in Wisconsin? For Remote Machine Vision Engineer jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Remote Machine Vision Engineer jobs in Wisconsin look for? The top searched job categories for Remote Machine Vision Engineer jobs in Wisconsin are:
What cities in Wisconsin are hiring for Remote Machine Vision Engineer jobs? Cities in Wisconsin with the most Remote Machine Vision Engineer job openings:
Remote Machine Vision Engineer jobs near you
Infographic showing various Remote Machine Vision Engineer job openings in Wisconsin as of July 2026, with employment types broken down into 89% Full Time, and 11% Part Time. Highlights an 100% Remote job distribution.
Lead Machine Learning Engineer

Lead Machine Learning Engineer

Serve Robotics

On-site, Remote

$225K - $260K/yr

Full-time

Re-posted 13 days ago

Job description

At Serve Robotics, we're reimagining how things move in cities. Our personable sidewalk robot is our vision for the future. It's designed to take deliveries away from congested streets, make deliveries available to more people, and benefit local businesses.
The Serve fleet has been delighting merchants, customers, and pedestrians along the way in Los Angeles, Miami, Dallas, Atlanta and Chicago while doing commercial deliveries. We're looking for talented individuals who will grow robotic deliveries from surprising novelty to efficient ubiquity.
Who We Are
We are tech industry veterans in software, hardware, and design who are pooling our skills to build the future we want to live in. We are solving real-world problems leveraging robotics, machine learning and computer vision, among other disciplines, with a mindful eye towards the end-to-end user experience. Our team is agile, diverse, and driven. We believe that the best way to solve complicated dynamic problems is collaboratively and respectfully.
This role develops and scales large-scale machine learning training systems for multimodal robotics data, enabling the creation of high-performance autonomy models. By optimizing distributed training pipelines, neural network architectures, and data processing workflows, the position improves training efficiency, accelerates model iteration, and maximizes GPU utilization. The role collaborates closely with ML researchers and infrastructure teams, influencing the design, deployment, and performance of end-to-end autonomy models and the large-scale data pipelines that support them.
Responsibilities
  • Design and maintain training systems that can process and learn from petabyte-scale multimodal datasets (e.g., video and point cloud data). This includes ensuring data is efficiently loaded, distributed, and processed across large GPU clusters.
  • Identify and resolve bottlenecks in the training pipeline, including data loading, preprocessing, model computation, and inter-node communication, to maximize GPU utilization and reduce training time.
  • Work with the ML team to develop and refine neural network architectures suitable for autonomy tasks, particularly those handling high-dimensional and sequential sensor data.
  • Create and adjust loss functions and training strategies that help the model learn effectively from complex multimodal inputs and improve autonomy performance.
  • Configure, monitor, and maintain large-scale distributed training jobs across multiple machines and GPUs, ensuring stability, fault tolerance, and efficient resource usage.
  • Implement scalable systems to preprocess, transform, and augment large robotics datasets so that they are suitable for model training.
  • Work closely with ML scientists and other engineers to integrate new models, experiments, and training approaches into the production training pipeline.
  • Analyze training metrics, model outputs, and experiment logs to assess model performance and guide improvements in architecture, data usage, or training strategies.
  • Develop tools and workflows that allow teams to run experiments, track results, and iterate quickly on new model ideas or training approaches.

Qualifications
  • Master's or PhD in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a closely related technical discipline.
  • Minimum of 5 years of professional experience developing, training, and deploying machine learning models in production environments.
  • Hands-on experience training machine learning models across multiple GPUs or compute nodes, including familiarity with distributed training frameworks and large dataset handling.
  • Strong programming skills in Python for implementing machine learning models, data pipelines, and training workflows.
  • Solid knowledge of core concepts such as neural networks, optimization algorithms, loss functions, model evaluation, and training methodologies.

What Makes You Stand out
  • Experience identifying and resolving training bottlenecks related to compute utilization, memory usage, and data throughput in machine learning systems.
  • Experience training machine learning models on robotics or autonomous driving datasets involving multimodal sensor inputs such as camera video, LiDAR point clouds, radar, or telemetry data.
  • Experience developing models that combine multiple data modalities (e.g., images, point clouds, and structured sensor data) into a unified learning system.
  • Peer-reviewed publications or significant research contributions in machine learning, robotics, or related areas.

*Please note: The listed base salary range applies to candidates based in the US. Compensation may vary depending on location, experience, and role alignment. We are open to qualified candidates working remotely in Canada
  • Canada - ALL: $177k - $215k CAD

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